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Record W6997284009

We were outsiders : the Metis and residential schools

2007· dissertation· en· W6997284009 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2007
Typedissertation
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Work (physics)Agency (philosophy)Action (physics)Perspective (graphical)
DOInot available

Abstract

fetched live from OpenAlex

This study looks at how the Métis were admitted to and discharged from the schools despite government policies lirniting their attendance.It also looks at how the Métis were treated at the schools and the impact that the schools have on cunent generations of Métis people.The study also reflects on the use of traumatic histories, Métis research rnethods and the state of Residential School history in Canada.The Government of Canada did not encourage Métis attendance and wanted to eliminate any federal responsibility towards supporting the Métis in Canada.Regardless, Métis attended the schools and generations of Métis people continue to be influenced by the intergenerational impacts of these schools today.The Métis were treated as outsiders in Residential Schools; they were treated differently by both teachers and administrators.The treatment of Métis students often mirrored how tliey were treated in their communities.Canada's agenda towards Aboriginal people disintegrated the relationship between government and the Métis, and Residential Schools were another way that the Métis were negatively affected by Canada's legacy of mistreating generations of Aboriginal people.It is intended for this study to reflect what Residential Schools meant to Métis lives fiom a Métis context.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.651

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0270.012
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0160.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.246
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractno

Explore more

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